Panel Data Research Center, Keio University
PDRC Discussion Paper Series

Intergenerational effect of father's job loss on children's educational attainments
in JapanKazuma Sato
19 March, 2020
DP2019-007
https://www.pdrc.keio.ac.jp/en/publications/dp/6203/

Panel Data Research Center, Keio University
2-15-45 Mita, Minato-ku, Tokyo 108-8345, Japan
info@pdrc.keio.ac.jp
19 March, 2020

Intergenerational effect of father's job loss on children's educational attainments in Japan
Kazuma Sato
PDRC Keio DP2019-007
19 March, 2020
JEL Classification: E24
Keywords: Father's job loss;Children's educational attainments

Abstract
This study attempted to explore the impact of the father's job loss on children's educational attainments
by using Keio Household Panel Survey (KHPS), which provides representative panel data for Japan. As
the intergenerational effect of father's job loss has not been examined in Japan so much because of thedata shortage, the results of this study can provide new empirical evidence. The analysis results present
four findings. First, the father's job loss has a negative relationship with the children's educational
attainments, and it decreases the year of education of children primarily by reducing university
graduates. This result is robust, even in using several matching methods. Second, the father's job loss
decreases male and female children's educational attainments, mainly through reducing university
graduates. The negative effect of the father's job loss is more substantial for the case of women. Third,
the father's job loss decreases first and second children's educational attainments mainly throughreducing university graduates. Fourth, the negative effect of the father's job loss on children's
educational attainments is observed even after the decline of the father's income is taken into accounts.

Kazuma Sato
Faculty of Political Science, Takushoku University
Kohinata 3-4-14, Bunkyo-ku, Tokyo 112-8585
ksqwt864@gmail.com

Acknowledgement: I appreciate the valuable comments from Yoshio Higuchi and Isamu Yamamoto.
The data for this analysis, Japan Household Panel Survey (JHPS/KHPS), was provided by the Keio
University Panel Data Research Center. This work was supported by JSPS Grants-in-Aid for Scientific
Research (KAKENHI) in Japan (17H06086).

Intergenerational effect of father's job loss onchildren's educational attainments in Japan*
Kazuma Sato**
Abstract
This study attempted to explore the impact of the father's job loss on children's educational attainments
by using Keio Household Panel Survey (KHPS), which provides representative panel data for Japan.
As the intergenerational effect of father's job loss has not been examined in Japan so much because of
the data shortage, the results of this study can provide new empirical evidence. The analysis resultspresent four findings. First, the father's job loss has a negative relationship with the children's
educational attainments, and it decreases the year of education of children primarily by reducing
university graduates. This result is robust, even in using several matching methods. Second, the father's
job loss decreases male and female children's educational attainments, mainly through reducing
university graduates. The negative effect of the father's job loss is more substantial for the case of
women. Third, the father's job loss decreases first and second children's educational attainments
mainly through reducing university graduates. Fourth, the negative effect of the father's job loss onchildren's educational attainments is observed even after the decline of the father's income is taken
into accounts.
Key words: Father's job loss, Children's educational attainments* I appreciate the valuable comments from Yoshio Higuchi and Isamu Yamamoto. The data for this analysis, Japan

Household Panel Survey (JHPS/KHPS), was provided by the Keio University Panel Data Research Center. This work
was supported by JSPS Grants-in-Aid for Scientific Research (KAKENHI) in Japan (17H06086).
** * Faculty of Political Science, Takushoku University, Kohinata 3-4-14, Bunkyo-ku, Tokyo 112-8585, Japan or
ksqwt864@gmail.com

11. Introduction
How will the father's job loss affect the children's educational attainment? This question related tointergenerational effect of job loss is a topic of growing interest1. Father's job loss is considered toharm children's educational attainment through several pathways. First, as the job loss of father, whois the primary earner in the household, brings persistent income fall (Jacobson et al., 1993; Stevens
1997). This income fall makes it difficult for parents to support the pursuits of education of children
financially. Second, since parental job loss has negatively associated with not only children's
educational performance (Rege et al., 2011), educational ambitions (Andersen, 2013), but also
educational outcomes (Brand and Thomas, 2014; Coelli, 2011), the likelihood of further educational
attainment of the children can be less likely. Third, parental job loss harms the children's health andwellbeing (Bubonya et al., 2017; Lindo 2011; Kohara et al., 2019; Schaller and Zerpa 2015), time of
the children allocated to study might be decline. Lastly, because father's job loss is negatively relatedwith children's non-cognitive skills which are considered to have significant impact on success on the
educational achievements and the outcomes in labor market (Cunha and Heckman, 2007; Heckman etal., 2006; Peter 2016), educational performance of the children whose father experienced job loss
might be decline. From these results, the father's job loss might harm their children's educational
attainment and might increase the disparities in education in the next generation. Several studies haveexamined the relationship between parental job loss and children's educational attainment empiricallyand they showed that parental job loss was negatively associated with children's educational attainment
in the United States (Page et al. 2009; Kalil and Wightman 2009), Canada (Coelli 2011), and Germany(Lindemann and Gangl 2019). However, most of the empirical results have used data from Westerncountries, and it remains unclear whether the same results would be obtained in other countries.
By examining the association between father's job loss and children's educational attainments inJapan, this study extends the existing scholarly literature on parental job loss and children's educational
achievements in four ways. First, to the best of my knowledge, this is the first study which examines
the relationship between father's job loss and children's educational attainments in Japan. Although
there are studies which examine the association of parental job loss and health of children (Kohara etal. 2019) and childbirth (Sato 2018), there is no study which investigates the effect of father's job loss
on children's educational attainments2. Thus, the present study contributes to the accumulation of
empirical research in the field.
Second, this study uses all experiences of job loss of father after he became 15 years old by utilizing
the retrospective school and work history record. The data used in this study is Keio Household Panel

There are plenty of studies which examined the relationship between parental earning level and earning level ofchildren. Solon (1992) and Zimmerman (1992) are examples of representative research, and Solon (1999) and
Björklund and Jäntti (2011) provide a comprehensive survey of this field.
2 Nozaki et al. (2018) examined the relationship between parental income and children's educational performance,
and they showed that parental income is positively correlated with children's educational performance.
12Data (KHPS), which provides representative panel data for Japan. The advantage of this data is that it
surveys school and work history of respondents and their spouses (if present) after 15 years old
retrospectively. It enables us to keep track of all experiences of job loss after 15 years old. Besides,
the data surveys the final educational background and birth year of all children, including those who
do not live together. By linking these variables, the effect of father's job loss on the children's
educational attainments is examined. In particular, a variable regarding whether the father experienced
job loss by the age of 15 when the child finished compulsory education is utilized in the analysis. By
using this variable, the present study focuses on how the father's experience of job loss affects
children's decision to go on to higher education after compulsory education.
Third, this study uses not only ordinary least squares (OLS) and logit models but also several
matching methods to identify the causal effect of the father's job loss on children's educational
attainments. Propensity score weighting (PSW) (Hirano and Imbens 2001), propensity score matching(PSM) (Heckman et al. 1997), and entropy balancing (Hainmueller 2011, 2012; Hainmueller and Xu
2013) are used for the analysis. In comparison with OLS and logit model, these matching methods
have an advantage, which allows the researcher to compare educational attainments of children whose
father experienced job loss with children whose father did not but had similar attributes. Thus, as
matching methods compare children with the same characteristics, the effect of father's job loss canbe examined more precisely.
Fourth, the several important determinants of children's educational attainments are controlled to
examine the effect of the father's job loss precisely. Educational achievements of parents are controlled
because there is a robust intergenerational relationship between the parental level of schooling andchildren's level of education (Hertz et al. 2007). Besides, educational attainments of grandparents arealso used as independent variables to control family background. Thus, the analysis considers therelationship between educational experiences over three generations. While there are restrictions on
the variables that can be used because of mainly using the retrospective school and work history recordof KHPS, the parental employment statuses when children were 15 years old are also controlled.
The remainder of this paper is organized as follows. The next section describes the data used in thisstudy. Section 3 explains the study’s empirical strategy, Section 4 elucidates the estimation results, andSection 5 provides concluding remarks.
2. Data
The data used in this study is KHPS, which investigates families, income, employment, and type ofresidence in Japan. The KHPS employs a two-step, stratified sampling method. The survey was first
conducted on January 31, 2004 with 4005 male and female respondents aged 20 to 69 years. The
survey is conducted annually, with data from 2018 being the latest data available. In 2007 and 2012,
new sample cohorts were added to supplement the attrition of samples in a similar survey method.
3

Data from 2004 to 2018 are used in the study.
There are two advantages to using KHPS. First, it surveys the respondents’ school and work history
from age 15 to the present retrospectively at the first survey of each cohort3. Respondents select fromthe following eight choices at each age from 15 to the present4: "attended school", "job seeking","temporary work", "regular employment", "self-employed or free-lance professional", "working athome", "worker at family business", and "changed job or school". From these choices, if the
respondents select “temporary work”, “regular employment”, “self-employed or free-lance
professional”, “working at home”, or “worker at family business”, it is defined as working. On thecontrary, if the respondents select “job seeking” or “attended school”, it is defined as being in an
unemployed state. In addition, it defines that it is in the state of unemployment when neither choice ischosen5. Of these working states, the case where a married man under 59 shifts from working tounemployment is defined as father’s job loss and used as a key variable6. In particular, this study
focusses the father's experience of job loss before children finish compulsory education under the ageof 15. Limiting to the above father's job loss allows us to examine how father's job loss affect thechildren’s decision to advance to further school after completing compulsory education.
In using the father's job loss, the limitation of this variable should be noted. Coelli (2011) and Pageet al (2009), which examined the effect of father's job loss on children's educational attainments, used
the job loss in case of business closing and layoff. This is because the job loss due to business closing
and layoff can be regarded as exogeneous employment shock and it enables to separate the effect of
the innate family background characteristics and to examine the causal effect of father's job loss onchildren's educational attainments. In contrast to this, as school and work history record of KHPS can’t
identify the reason of job loss, it is difficult to conduct similar analysis with Coelli (2011) and Page etal (2009). Despite of this limitation, as panel data that provides abundant samples of job loss is rare in
Japan, KHPS represents the best option for this study’s analyses.
The second advantage of using KHPS is that it surveys final academic background, birth year, andgender of all children with or without living together in 2017 and 20187. By using this record, all

As a similar school and work history record is available for the spouse, the experience of job loss of a spouse is also
used for the analysis. When the respondents are women, the experience of job loss of her spouse is regarded as thefather's job loss and utilized for crucial variables.
4 This question was investigated in 2004 at the start of the survey and in 2007 and 2012 when a new cohort wasadded.
5 There is no choice to indicate non-labor force in the school and work history record of KHPS. For this reason, thecase where none of the choices was chosen was regarded as a non-labor force. In this case, however, there is a riskthat the non-workforce will include no answer. However, Sato (2012, 2018), which used similar job loss by using
school and work history record of KHPS and examined the effect of job loss on wife's additional worker effect andchildbirth, indicated that husband's job loss stimulated wife to work and decreased the likelihood of new childbirth.
As these results are consistent with previous studies, the job loss variable made by the school and work history record
can be said to be reliable even if it might include missing values in non-labor.
6 In order to exclude job loss due to mandatory retirement, the sample of father was limited to 59 years or younger.
7 The questionnaire regarding the final educational background can identify whether a child is in school. In case ofchildren in schooling, their current stages of education are surveyed.
34children who completed their schooling are analyzed. Three dummy variables regarding with final
academic background are made: high school graduate, junior college or specialized school graduate,
and university graduate or more. When multiple children who completed education were at home, thevariables were made for all of them.
The samples included for analysis were limited to respondents for whom no missing values wererecorded in the above-mentioned relevant variables. The analysis sample is 1530 children.
3. Estimation methods
3.1 Econometric modelThis study attempted to explore the relationship between father’s job loss and children’s educational
attainments. The econometric model used to examine the relationship was:𝐸𝑑𝑢𝑖 = 𝛼 + 𝛽𝐽𝑜𝑏𝑙𝑜𝑠𝑠𝑖 + 𝛾𝑋𝑖 + 𝜀𝑖

(1)

In the above model, 𝐸𝑑𝑢𝑖 represents the final educational background of a child i. In the analysis,
three dummy variables of final educational background of children and year of education of children
are used for dependent variables8. 𝐽𝑜𝑏𝑙𝑜𝑠𝑠𝑖 indicates dummy variable of job loss of father of a childi. This dummy variable becomes 1 if fathers experienced job loss before the age of 15 when children
finished compulsory education and becomes 0 otherwise9. The coefficients of 𝐽𝑜𝑏𝑙𝑜𝑠𝑠𝑖 are primaryinterest in the examination of whether or not the father's job loss affect the children’s decision toadvance to further school after completing compulsory education. 𝑋𝑖 indicates the attributes ofchildren and household, including gender of children, birth order of children, number of brothers andsisters, birth cohort dummies of children, unemployment rate when children were 15 years old, total
years of work experience of father and mother when children were 15 years old, dummy variables offull time employment, part time employment, or self-employment of mother when children were 15
years old, final educational background of parent, and final educational background of grandparent.
𝜀𝑖 indicates error term. Model (1) is estimated by the Logit model and OLS.
In order to check the robustness of the estimated results by model (1), matching methods are also
used. When estimating the effects of father's job loss on children's educational attainments, the averagetreatment effect on the treated (ATT) is as follows.

The year of education of children is defined as follows: junior high school graduates are 9 years, high school
graduates are 12 years, junior college or specialized school graduates are 14 years, university graduates are 16 years,
and graduates are 18 years.
9 While the analysis using the father's job loss variable which becomes 1 if fathers experienced job loss before
children were 18 and becomes 0 otherwise was also conducted, the estimated results were almost same with Table 2
and Table 3.
8

5

ATT = E[𝑌1𝑖 − 𝑌0𝑖 |𝐷𝑖 = 1] = E[𝑌1𝑖 |𝐷𝑖 = 1] − E[𝑌0𝑖 |𝐷𝑖 = 1](2)

In equation (2), 𝑌𝑖 indicates children’s educational attainments, where 𝑌1 indicates the value atthe time when father experienced job loss and 𝑌0 is the value at the time when father did notexperience job loss and continued to work. 𝐷 indicates whether or not father experienced job loss.
𝐷 = 1 indicates father experienced job loss before his children completed compulsory education(treatment group) and 𝐷 = 0 indicates that father did not experience job loss and continued to work
(control group). In (2), E[𝑌0𝑖 |𝐷𝑖 = 1] is a value that assumes that father experienced job loss, and its
value is counterfactual. PSW solves this problem by using a weighted control group, which can replace
E[𝑌0𝑖 |𝐷𝑖 = 1].

E[𝑌0𝑖 |𝐷̂𝑖 = 1] =∑{𝑖|𝐷=0} 𝑌0𝑖 𝑑𝑖∑{𝑖|𝐷=0} 𝑑𝑖(3)

In (3), 𝑑𝑖 is the sampling weight for the control group and 𝑑𝑖 = 𝑃(𝑋)⁄1 − 𝑃(𝑋). 𝑃(𝑋) indicatespropensity score that is the likelihood to be a treatment group estimated by the logit model which
employs attributes of children and household as covariates. In the analysis, PSW is used to examine
the effect of father’s job loss on children’s educational attainments. In addition, PSM applying kernel
matching is also employed.
In addition to these matching methods, entropy balancing, which controls the differences of
attributes of children and household between treatment and control groups by using sampling weight
as like PSW, is also used. However, in entropy balancing, sampling weight is induced in the different
way from PSW. Sampling weight of entropy balancing is induced by the constraint equations which
satisfy an exact balance between the first and second moments of attributes of children and householdin treatment and control groups. Both the mean and variance of the attributes among the treatment andcontrol groups are equated by using the first and second attribute moments10. In order to equate themean and variance among the treatment and control groups, this analysis also utilizes the first andsecond attribute moments.
3.2 Basic statistics before and after matching
Table 1 indicates the mean values of dependent and independent variables used in the analysis.
Column (A) showed the values when fathers experienced job loss (treatment group), column (B)The detailed description about sampling weight of the entropy balancing is available on Hainmueller and Xu(2013).
106

indicates the values when fathers did not experience job loss (control group), and column (C)represents the differences of values of column (A) and column (B). While column (D) indicates themean values of the control group weighted by PSW, column (F) shows those weighted by PSM.
Column (H) indicates the mean values of the control group weighted by entropy balancing. Column(E), (G), and (I) show the differences between column (A) and column (D), (F), and (H), respectively.
Column (C), which is the difference of column (A) and (B) before matching, represent thatsignificant differences exist in the means of educational attainments of children, birth cohort ofchildren, unemployment rate when children were 15 years old, total years of work experience of father,father's ratio of more than university graduates, proportion of the junior college or specialized school
graduates of grandmother on father's side, and rate of the junior college or specialized school graduatesof grandfather on mother's side. However, as shown in column (E), (G), and (I), all of the statisticallysignificant differences of the independent variables disappear after matching. This result indicates thatmatching methods appropriately control for differences in attributes of children and households among
the treatment and control group. In contrast, the statistically significant differences of dependent
variables among treatment and control group still exist even after matching, indicating that whilechildren whose father experienced job loss are less likely to graduate university, they are likely tocomplete their education at high school. Thus, it can be said that children's educational attainments
tend to be lower when their fathers experienced job loss.
4. Empirical results
4.1 Effect of father’s job loss on children’s educational attainments
Table 2 indicates the results of logit model and values of Table 2 are the marginal effects11. Panel(A) of Table 2 indicates the estimated results on whether the child graduated from university. All
marginal effects of a father's job loss are negatively significant, meaning that children whose father
experienced job loss are less likely to graduate university. In contrast, panel (B) of Table 2, which isthe estimated results on whether the child graduated from junior college or specialized school,
indicates that all marginal effects of father's job loss are not statistically significant. This result reveals
that the father's job loss does not affect whether the child graduated from junior college or specialized
school. Panel (C) of Table 2, which is the estimated results on whether the child graduated from highschool, indicates that all marginal effects of the father's job loss are positively significant. This resultshows that children whose father experienced job loss are likely to graduate from high school.
Table 3 indicates the results of matching methods. All of the estimated effects of Table 3 areconsistent with the results of Table 2. While the father's job loss has a negative association withchildren's graduation from university, it has a positive relationship with children's graduation from

11

Results showing estimates for all variables in Table 2 are given in Appendix A, B, and C.

7

high school. Regarding the junior college or specialized school graduate, the father's job loss is not
related to it. Table 4 indicate the results of OLS and matching methods when using the year of
education of children as the dependent variable. All coefficients of the father's job loss are negatively
significant, indicating that the father's job loss decreases the year of education of children.
Summarizing the above results, it is concluded that the father's job loss has a negative relationshipwith the children's educational attainments. Father's job loss decreases the year of education ofchildren primarily by reducing university graduates. Although the number of children who graduatedhigh school is increased, it might be because the number of children who gave up going on to
university and finished education in high school increased.
4.2 Additional analysis: The impact of the father's job loss by the gender and birth order ofchildren
The results so far clearly show that the father's job loss is negatively related to children's educational
attainments. Although it provides new empirical evidence of the intergenerational effect of father's job
loss on children's educational attainments in Japan, there are still questions regarding its effect: does
the impact of father's job loss depend on gender and birth order of children? To answer this question,
the additional analysis which divides sample by gender or birth order is conducted.
Table 5 indicate the estimated results by gender of children. Estimation results of Panel (A) of Table
5 when a child is a man show that father's job loss is negatively associated with the likelihood of
graduating university. However, the father's job loss does not have a statistically significant clear
relationship with the other educational attainments. These results indicate that the father's job loss
mainly deceases children's university graduates when a child is a man. Considering that the father's
job loss does not have a definite significant relationship with a year of education of children, its
negative impact on educational attainments could be moderate. Estimation results of Panel (B) of Table
5 when the child is a woman show that while father's job loss is negatively related to the likelihood of
graduating university, it is positively associated with that of graduating high school. Besides, thefather's job loss has a negatively significant association with the year of education. These results revealthat when the child is a woman, father's job loss decreases children's educational attainments because
the negative impact of father's job loss on university graduates seems to be larger than the positiveeffect on high school graduates.
Summarizing the above results, the father's job loss decreases male and female children's
educational attainments mainly through reducing university graduates. The relationship between thefather's job loss and children's educational attainments is relatively definite in the case of women.
Table 6 indicate the estimated results by birth order of children. The sample is split when the childis the first or second child. Analysis after the third child cannot be conducted due to the small sample
size. Estimation results of Panel (A) of Table 6 when the subject is a first child show that a father's job
8loss is negatively associated with the likelihood of graduating university. However, the father's job
loss does not have a statistically significant relationship with most of the other educational attainments.
These results indicate that the father's job loss mainly deceases children's university graduates when
the subject is a first child. Estimation results of Panel (B) of Table 6 when the subject is a second childshow a clear significant relationship between father's job loss and children's educational attainments.
While the father's job loss is negatively related to the likelihood of graduating from university, it ispositively associated with that of graduating high school. Considering that father's job loss isnegatively correlated with year of education, the negative impact of the father's job loss on graduationfrom university is considered to be relatively large.
Summarizing the above results, father's job loss decreases first and second children's educational
attainments mainly through reducing university graduates. The relationship between the father's job
loss and children's educational attainments is relatively definite in the case of the second child.
4.3 Additional analysis: The impact of the father's job loss after considering the father's earning
The analysis so far has mainly analyzed the impact of the father's job loss but did not examine thecause of the effect. One of the causes of this effect is considered to be a decrease in the father's income.
Financial constraint by the father's job loss is likely to suppress further education attainment ofchildren. An additional analysis which adds the father's earning to the independent variables isconducted to check this point. In the analysis, the period of the analysis is limited from 2004 to 2018
because the father's earning can only be observed after 200412. Besides, as the sample size of thefather's job loss is so small at 30 or less, we use the logit model and OLS.
The results of Table 7 estimated by the logit model and OLS show that children whose father
experienced job loss are less likely to graduate university even after controlling the father's earning.
Besides, the estimated results show that the father's job loss decreases the year of education of children
even after controlling the father's earning. These results indicate that the negative effect of the father's
job loss on children's educational attainments is caused by not the decline of father's earning but theother factors. As previous studies indicate, other factors are considered to be the decrease in children’s
educational performance (Rege et al., 2011) and educational ambitions (Andersen, 2013), deteriorationof children’s health, wellbeing, and non-cognitive skill (Bubonya et al., 2017; Lindo 2011; Kohara etal., 2019; Peter 2016; Schaller and Zerpa 2015).
4.4 Robustness check
To check the robustness of the estimated results, the additional analysis which uses the other father’s

While the average earning of the father who experienced a job loss is 3.30 million yen, the average earning of thefather who did not experience a job loss is 6.71 million yen. These numbers clearly show that job loss has a negative
effect on the father’s income.
12

9

job loss is conducted. The analysis so far used the father’s job loss, which occurred before children
finished their compulsory education. In the analysis, father’s job loss was assumed to cause persistent
income decline, decrease in children’s educational performance and educational ambitions, anddeterioration of children’s health, wellbeing, and non-cognitive skill, resulting in a decrease inchildren's educational attainments. However, since father's job loss was caused not only by involuntaryreasons but also by voluntary reasons, the effect of the father's job loss might include some bias due
to unobserved heterogeneity. To check this, the analysis adding a father's job loss, which occurred afterchildren completed their education is conducted. Most of the children would finish their education
until they are 25 years old because the age of graduating from university in Japan is about 22 years
old. Thus, the father's job loss, which occurred after children were over 25 years old, would not affectchildren's educational attainments. However, if it has a significant relationship with children's
educational achievements, it can be considered to capture unobserved heterogeneity.
The estimated result including father's job loss which occurred after children finished theireducation is presented at Table 81314. The models used here are logit and OLS. In the model, the father's
job loss occurred before children finished compulsory education, and all independent variables arealso included. All coefficients of the father's job loss after children finished education are notstatistically significant. This result indicates that the father's job loss after children finished education
does not include unobserved heterogeneity. Although the estimation results are not reported in Table
8, the effect of the father's job loss after the child's age is over 24 or 26 years old was also analyzed.
Still, in any case, the father's job loss was not statistically significant. These results increase thereliability that the father's job loss variable appropriately captures the decline in income and thenegative impact on children.
5. Conclusion
This study attempted to explore the impact of the father's job loss on children's educational
attainments by using KHPS. As the intergenerational effect of father's job loss has not been examinedin Japan so much because of the data shortage, the results of this study can provide new empiricalevidence. The analysis results indicate three points. First, the father's job loss has a negative
relationship with the children's educational attainments, and it decreases the year of education ofchildren primarily by reducing university graduates. This result is robust, even in using several
matching methods. Second, the father's job loss decreases male and female children's educational
attainments, mainly through reducing university graduates. The relationship between the father's job
loss and children's educational attainments is relatively definite in the case of women. Third, theIn order to check the exogeneity of father's job loss, similar method is employed at Coelli (2011).
When father experienced job loss before children finish their compulsory education, father's job loss which
occurred after children finished their education is set to zero.
13
14

10

father's job loss decreases first and second children's educational attainments mainly through reducing
university graduates.
The results of this study clearly showed that the father's job loss could have a negativeintergenerational effect on children's educational attainments. As educational attainment is an essential
factor for success in the labor market, a father's job loss is also expected to affect children's outcomesadversely in the labor market. This point was examined by Oreopoulos et al. (2008), and they showedthat children whose father experienced job loss were likely to earn lower and receive welfare support.
In the case of Japan, as the relationship between a father's job loss and children's outcomes in the labormarket has not been examined, the next step in this study is to analyze this point.
Comparing with previous studies of Western countries, this study provided new findings. Page et al.
(2009) and Kalil and Wightman (2009), which examined the effect of parental job loss by using thePanel Study of Income Dynamics (PSID), showed that parental job loss had a remarkable negative
impact on children in case of relatively lower socioeconomic status. In contrast, the present study
using Japanese data showed that the father's job loss hurt children's educational attainments averagely.
This might be because life-long employment practices remain in Japan, and the negative impact of job
loss is prominent, as supported by Sato (2015).
Finally, outstanding issues should be noted. In Japan, student loan for university advancement is
widely available, and this can be useful to solve the financial constraints due to the father's job loss.
However, as KHPS does not survey whether or not children used student loan, it is difficult to examine
how the student loan mitigate the financial constraints. In addition to this, KHPS does not survey
children's educational performances at all. As educational achievements are one of the critical
determinants, it will be better to include these variables in covariates. Since it may be challenging todeal with these problems in KHPS, re-analysis using other data will be the next step.

11

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13

Table 1. Basic statistics(A)(B)
Unweighted

Father's job loss
=1
Father's job loss
=0

(C)

(D)

(E)

(F)

(G)

Weighted by
Weighted by
PSW
PSW(A)-(B)(A)-(D)
Father's job loss
Father's job loss
=0=0(A)-(F)(H)(I)

Weighted byentropy balancing(A)-(H)
Father's job loss
=0

Educational attainment of children
University graduate or more

0.16

0.35

-0.19***

0.38-0.21***

0.37-0.21***

0.37

Junior college or specialized school graduate

0.29

0.26

0.03

0.25

0.04

0.24

0.05

0.25

-0.21***
0.04

High school graduate

0.48

0.33

0.15**

0.33

0.15**

0.34

0.14**

0.33

0.15**

Year of education

13.03

13.81

-0.78***

13.92-0.89***

13.87-0.84***

13.91-0.88***

Gender of children (men=1, women=0)

0.50

0.41

0.09

0.5

0.00

0.49

0.01

0.5

0.00

Birth order of children

1.50

1.57

-0.07

1.5

0.00

1.5

0.00

1.5

0.00

Number of brothers and sisters

1.52

1.37

0.14

1.51

0.01

1.46

0.06

1.52

0.00

Birth cohort of children: 1970-1979

0.16

0.24

-0.08

0.15

0.01

0.18

-0.02

0.16

0.00

Birth cohort of children: 1980-1989

0.24

0.36

-0.11*

0.24

0.00

0.28

-0.04

0.24

0.00

Birth cohort of children: 1990 -

0.53

0.34

0.19***

0.55

-0.02

0.48

0.05

0.53

0.00

Unemployment rate at age 15

4.07

3.76

0.31**

4.1

-0.03

3.99

0.08

4.07

0.00

Total years of work experience of father

16.19

19.47

-3.28***

15.42

0.77

17

-0.81

16.19

0.00

Total years of work experience of father

9.05

10.21

-1.16

8.78

0.27

9.13

-0.08

9.05

0.00

Dummy of full time employment of mother

0.19

0.17

0.02

0.18

0.01

0.17

0.02

0.19

0.00

Dummy of part time employment of mother

0.37

0.34

0.03

0.37

0.00

0.38

-0.01

0.37

0.00

Dummy of self-employment of mother

0.19

0.20

-0.01

0.19

0.00

0.19

0.00

0.19

0.00

Individual attributes of children

Work experience of parent at age 15

Educational attainments of parent
Father: Junior college or specialized school graduate

0.29

0.21

0.08

0.29

0.00

0.26

0.03

0.29

0.00

Father: University graduate or more

0.47

0.34

0.13**

0.13

0.34

0.12

0.35

0.13

0.34

Mother: Junior college or specialized school graduate

0.06

0.06

0.01

0.06

0.00

0.06

0.00

0.06

0.00

Mother: University graduate or more

0.13

0.09

0.04

0.49

-0.36

0.44

-0.31

0.47

-0.34

Grandfather on father's side : Junior college or specialized school graduate

0.06

0.05

0.02

0.06

0.00

0.05

0.01

0.06

0.00

Grandfather on father's side : University or graduate school

0.03

0.07

-0.04

0.03

0.00

0.05

-0.02

0.03

0.00

Grandmother on father's side: Junior college or specialized school graduate

0.13

0.05

0.07**

0.15

-0.02

0.11

0.02

0.13

0.00

Grandmother on father's side: University or graduate school

0.02

0.01

0.01

0.02

0.00

0.02

0.00

0.02

0.00

Grandfather on mother's side: Junior college or specialized school graduate

0.11

0.04

0.07**

0.1

0.01

0.11

0.00

0.11

0.00

Grandfather on mother's side: University or graduate school

0.10

0.09

0.01

0.12

-0.02

0.09

0.01

0.1

0.00

Grandmother on mother's side: Junior college or specialized school graduate

0.06

0.06

0.00

0.06

0.00

0.07

-0.01

0.06

0.00

Grandmother on mother's side: University or graduate school

0.02

0.01

0.01

0.02

0.00

0.02

0.00

0.02

0.00

62

1,468

Educational attainments of grandparent

Observations

1,468

NOTES: *, **, and *** denote significance at the 10%, 5%, and 1% levels, respectively.

14

1,468

1,468

Table 2. Effect of father’s job loss on children’s educational attainments
estimated by Logit model
Panel (A) Educational attainment of child: University graduate or more
(1)

(2)

(3)

(4)

(5)

-0.235***-0.223***-0.221***-0.252***-0.253***(0.078)(0.076)(0.077)(0.077)(0.079)Individual attributes of child

No

Yes

Yes

Yes

Yes

Work experience of parent at age 15

No

No

Yes

Yes

Yes

Educational attainments of parent

No

No

No

Yes

Yes

Educational attainments of grandparent

No

No

No

No

Yes

Father's job loss

Estimation method
Log pseudolikelihood

Logit

Logit

Logit

Logit

Logit

-981.022-968.141-960.404-919.470-917.682

Observations

1,530

1,530

1,530

1,530

1,530

(4)

(5)

Panel (B) Educational attainment of child: Junior college or specialized school graduate(1)
Father's job loss

(2)

(3)

0.033

0.040

0.031

0.042

0.046

(0.055)(0.055)(0.057)(0.055)(0.056)

Individual attributes of child

No

Yes

Yes

Yes

Yes

Work experience of parent at age 15

No

No

Yes

Yes

Yes

Educational attainments of parent

No

No

No

Yes

Yes

Educational attainments of grandparent

No

No

No

No

Yes

Estimation method
Log pseudolikelihood

Logit

Logit

Logit

Logit

Logit

-872.600-853.230-850.717-843.611-842.771

Observations

1,530

1,530

1,530

1,530

1,530

(1)

(2)

(3)

(4)

(5)

0.143**

0.133**

0.143**

0.161***

0.148**(0.057)(0.060)(0.060)(0.059)(0.059)Individual attributes of child

No

Yes

Yes

Yes

Yes

Work experience of parent at age 15

No

No

Yes

Yes

Yes

Educational attainments of parent

No

No

No

Yes

Yes

Panel (C) Educational attainment of child: High school graduate
Father's job loss

Educational attainments of grandparent

No

No

No

No

Yes

Estimation method
Log pseudolikelihood

Logit

Logit

Logit

Logit

Logit

-974.313-965.566-963.685-948.299-942.687

Observations

1,530

1,530

1,530

1,530

1,530

NOTES: *, **, and *** denote significance at the 10%, 5%, and 1% levels, respectively

15

Table 3. Effect of father’s job loss on children’s educational attainments
estimated by PSW, PSM, and entropy balancing

University graduate or more

Junior college or specialized school graduate

High school graduate

Father's job loss

Father's job loss

Father's job loss

Entropy balancing

PSW

PSM

Observations-0.209***-0.215***-0.206***1,530(0.047)(0.059)(0.055)

0.038

0.039

0.046

(0.054)(0.065)(0.063)0.145**

0.156**

0.145**(0.058)(0.073)(0.073)

Notes: *, **, and *** denote significance at the 10%, 5%, and 1% levels, respectively.

16

1,530

1,530

Table 4. Effect of father’s job loss on children’s year of education estimated by OLS and matching methods

Dependent variable: Year of education of children
(1)

(2)

(3)

(4)

-0.827***-0.875***-0.889***-0.833***(0.250)(0.226)(0.277)(0.245)

Estimation method

OLS

Entropy balancing

PSW

PSM

R2

0.116

Observations

1,530

1,530

1,530

1,530

Father's job loss

Notes: *, **, and *** denote significance at the 10%, 5%, and 1% levels, respectively.

17

Table 5. Effect of father’s job loss on children’s educational attainments: estimates by child gender
Panel (A) gender of children=men
Logit
University graduate or more

Junior college or specialized school graduate

High school graduate

Father's job loss

Father's job loss

Father's job loss

Entropy balancing

PSW

PSM

Observations-0.251**

OLS-0.163**-0.171**-0.156*629(0.113)(0.065)(0.072)(0.080)0.114*

0.123*

0.122

0.127

(0.066)(0.065)(0.081)(0.095)

0.068

0.020

0.039

0.058

(0.077)(1.000)(0.110)-0.608*-0.436-0.491-0.306(0.341)(0.318)(0.399)(0.393)

OLS

Entropy balancing

PSW

PSM

Observations-0.231***-0.221**-0.261***901(0.108)(0.057)(0.088)(0.077)-0.005-0.055-0.062-0.020(0.086)(0.066)(0.089)(0.091)0.233***

0.277***

0.287***

0.285***(0.084)(0.064)(0.099)(0.100)-1.020***-1.148***-1.091***-1.144***(0.375)(0.296)(0.384)(0.337)(0.085)
Year of education of children

Father's job loss

629

629

629

Panel (B) gender of children=women
Logit
University graduate or more

Junior college or specialized school graduate

High school graduate

Year of education of children

Father's job loss

Father's job loss

Father's job loss

Father's job loss

-0.263**

Notes: *, **, and *** denote significance at the 10%, 5%, and 1% levels, respectively.
18

901

901

901

Table 6. Effect of father’s job loss on children’s educational attainments: estimates by birth order of children
Panel (A) Birth order of children=First child
Entropy balancing

PSW

PSM

Observations-0.142***-0.142**-0.125*833(0.087)(0.051)(0.071)(0.071)

0.095

0.097*

0.104

0.087

(0.065)(0.056)(0.075)(0.084)

0.046

0.029

0.032

0.020

(0.073)(0.085)(0.092)-0.338-0.393-0.407-0.412(0.322)(0.283)(0.340)(0.360)OLS

Entropy balancing

PSW

PSM

Observations-0.331***-0.390***-0.378***541(0.160)(0.060)(0.117)(0.138)

0.086

0.111

0.093

0.107

(0.110)(0.102)(0.137)(0.139)0.234**

0.297***

0.305**

0.282*(0.104)(0.066)(0.129)(0.146)-1.154***-1.347***-1.423***-1.349***(0.425)(0.277)(0.411)(0.463)

Logit
University graduate or more

Junior college or specialized school graduate

High school graduate

Father's job loss

Father's job loss

Father's job loss

OLS

-0.145*(0.076)
Year of education of children

Father's job loss

833

833

833

Panel (B) Birth order of children=Second child
Logit
University graduate or more

Junior college or specialized school graduate

High school graduate

Year of education of children

Father's job loss

Father's job loss

Father's job loss

Father's job loss

-0.366**

Notes: *, **, and *** denote significance at the 10%, 5%, and 1% levels, respectively.
19

541

541

541

Table 7. Effect of the father's job loss on children's educational attainments: estimates after considering the father's earning

University graduate or more

Junior college or specialized school graduate

High school graduate

Year of education of children

Father's job loss

Father's job loss

Father's job loss

Without father's earning

With father's earning

Logit

Logit

OLS

-0.495**-0.424**(0.206)(0.207)

0.085

0.053

(0.089)(0.089)0.135*

0.127(0.080)(0.082)Father's job loss

OLS

Observations
745

745

745

-0.989***-0.768**(0.367)(0.376)745

Notes: *, **, and *** denote significance at the 10%, 5%, and 1% levels, respectively. The period of the analysis is limited from 2004 to 2018 because thefather's earning can only be observed after 2004.

20

Table 8. Effect of father’s job loss which occurred after children finished their education on children’s educational attainments(1)

Junior college or
specialized school
graduate(2)-0.253***0.052

0.143**-0.808***(0.078)(0.056)(0.060)(0.253)-0.0030.026-0.0230.088(0.033)(0.030)(0.032)(0.145)

Estimation method

Logit

Logit

Logit

OLS

Log pseudolikelihood-911.361-839.527-936.215

Dependent variable

Father's job loss before children finish compulsory education
Father's job loss after children finish education

University graduate
or moreHigh school
graduate

Year of educationof children

(3)

(4)

R2
Observations

0.116
1,530

Notes: *, **, and *** denote significance at the 10%, 5%, and 1% levels, respectively.

21

1,530

1,530

1,530

Appendix A. Effect of father’s job loss on children’s educational attainments:
University graduate or more
Dependent variable:University graduate or more

(1)

Father's job loss

(2)

(3)

(4)

(5)

-0.235*** -0.223*** -0.221*** -0.252*** -0.253***(0.078)(0.076)(0.077)(0.077)(0.079)-0.044*-0.046*-0.042*-0.042*(0.025)(0.025)(0.024)(0.024)0.037**

0.042**

0.046**

0.044**(0.018)(0.019)(0.019)(0.019)-0.017-0.018-0.010-0.013(0.018)(0.019)(0.018)(0.018)

Individual attributes of children
Gender of children
Birth order of children
Number of brothers and sisters
Birth cohort of children:1970-1979-0.204*** -0.197*** -0.183*** -0.175***

Birth cohort of children:1980-1989-0.178*** -0.168** -0.166*** -0.155**

Birth cohort of children:1990--0.233*** -0.227*** -0.248*** -0.233***(0.052)(0.067)

Unemployment rate at age 15(0.051)(0.066)(0.048)(0.064)(0.048)(0.064)(0.065)(0.065)(0.063)

0.016

0.016

0.004

(0.063)0.003(0.021)(0.021)(0.021)(0.021)Work experience of parent at age 15
Total years of work experience of father
Total years of work experience of father
Dummy of full time employment of mother
Dummy of part time employment of mother
Dummy of self-employment of mother

0.002

0.002

0.002

(0.003)(0.003)(0.003)-0.006*** -0.005**-0.005**(0.002)(0.002)(0.002)

0.024

0.022

0.018

(0.044)(0.042)(0.043)-0.015

0.013

0.014

(0.034)(0.033)(0.033)-0.010

0.023

0.021

(0.047)(0.045)(0.045)

Educational attainments of parent
Mother: Junior college or specialized school graduate

0.090*** 0.083***

Mother: University graduate or more

0.233*** 0.224***(0.031)(0.042)Father: Junior college or specialized school graduate
Father: University graduate or more

(0.032)(0.043)

0.061

0.052

(0.051)(0.051)0.130*** 0.120***(0.027)(0.028)

Educational attainments of grandparent
Grandfather on father's side: Junior college or specialized school graduate

0.090*(0.051)

Grandfather on father's side: University graduate or more

-0.005(0.050)Grandmother on father's side: Junior college or specialized school graduate-0.033(0.049)Grandmother on father's side: University graduate or more

0.097
(0.104)Grandfather on mother's side: Junior college or specialized school graduate

0.051(0.056)Grandfather on mother's side: University graduate or more

0.034
(0.044)Grandmother on mother's side: Junior college or specialized school graduate-0.025(0.051)

Grandmother on mother's side: University graduate or more

0.066
(0.093)

Estimation method
Log pseudolikelihood

Logit

Logit

Logit

Logit

Logit

-981.022-968.141-960.404-914.097-911.366

Observations

1,530

1,530

1,530

1,530

1,530

Notes: *, **, and *** denote significance at the 10%, 5%, and 1% levels, respectively.
22

Appendix B. Effect of father’s job loss on children’s educational attainments:
Junior college or specialized school graduate
Dependent variable:Junior college or specialized school graduate

(1)

(2)

(3)

(4)

(5)

Father's job loss

0.033

0.040

0.031

0.042

0.046

(0.055)(0.055)(0.057)(0.055)(0.056)-0.040*-0.039*-0.041*-0.039*(0.023)(0.023)(0.023)(0.023)

0.005

0.007

0.007

0.007

(0.016)(0.017)(0.017)(0.017)

0.036**

0.038**

0.036**

0.036**(0.016)(0.016)(0.016)(0.016)

Individual attributes of children
Gender of children
Birth order of children
Number of brothers and sisters
Birth cohort of children:1970-1979

0.274*** 0.271*** 0.264*** 0.263***(0.072)(0.072)(0.072)(0.072)Birth cohort of children:1980-1989

0.213**

0.204**

0.203**

0.205**(0.083)(0.083)(0.083)(0.083)0.153*

0.139*

0.138*

0.139*(0.081)(0.081)(0.081)(0.081)Birth cohort of children:1990Unemployment rate at age 15

0.029

0.030

0.031

0.030

(0.020)(0.020)(0.020)(0.020)Work experience of parent at age 15
Total years of work experience of father
Total years of work experience of father
Dummy of full time employment of mother
Dummy of part time employment of mother
Dummy of self-employment of mother-0.003-0.002-0.002(0.003)(0.003)(0.003)

0.002

0.002

0.002

(0.002)(0.002)(0.002)

0.022

0.017

0.021

(0.042)(0.041)(0.041)

0.039

0.028

0.029

(0.032)(0.032)(0.032)-0.004-0.009-0.006(0.043)(0.043)(0.043)

Educational attainments of parent
Mother: Junior college or specialized school graduate-0.021-0.023(0.029)(0.030)Mother: University graduate or more

-0.175*** -0.180***(0.053)(0.053)

Father: Junior college or specialized school graduate

0.092**

0.091**(0.043)(0.044)

Father: University graduate or more

0.009

0.009

(0.027)(0.028)

Educational attainments of grandparent
Grandfather on father's side: Junior college or specialized school graduate-0.026(0.059)Grandfather on father's side: University graduate or more

0.012
(0.048)Grandmother on father's side: Junior college or specialized school graduate-0.034(0.053)

Grandmother on father's side: University graduate or more

-0.011(0.104)Grandfather on mother's side: Junior college or specialized school graduate-0.013(0.058)Grandfather on mother's side: University graduate or more

-0.009(0.045)Grandmother on mother's side: Junior college or specialized school graduate

0.041(0.050)Grandmother on mother's side: University graduate or more

0.121
(0.083)

Estimation method
Log pseudolikelihood

Logit

Logit

Logit

Logit

Logit

-872.600-853.230-841.396-839.907-974.313

Observations

1,530

1,530

1,530

1,530

1,530

Notes: *, **, and *** denote significance at the 10%, 5%, and 1% levels, respectively.
23

Appendix C. Effect of father’s job loss on children’s educational attainments:
High school graduate
Dependent variable:High school graduate
Father's job loss

(1)

(2)

(3)

(4)

(5)

0.143**

0.133**

0.143**

0.161***

0.148**(0.057)(0.060)(0.060)(0.059)(0.059)0.055**

0.055**

0.053**

0.048**(0.024)(0.024)(0.024)(0.024)-0.006-0.012-0.014-0.011(0.019)(0.020)(0.020)(0.020)Individual attributes of children
Gender of children
Birth order of children
Number of brothers and sisters
Birth cohort of children:1970-1979
Birth cohort of children:1980-1989
Birth cohort of children:1990Unemployment rate at age 15

0.009

0.009

0.002

0.006

(0.019)(0.019)(0.019)(0.019)

0.065

0.060

0.053

0.051

(0.055)(0.055)(0.051)(0.052)

0.045

0.039

0.033

0.024

(0.069)(0.068)(0.066)(0.066)0.121*

0.121*

0.132**

0.119*(0.068)(0.068)(0.066)(0.067)-0.032-0.033-0.024-0.020(0.021)(0.021)(0.021)(0.021)Work experience of parent at age 15
Total years of work experience of father
Total years of work experience of father
Dummy of full time employment of mother
Dummy of part time employment of mother
Dummy of self-employment of mother

0.002

0.002

0.001

(0.003)(0.003)(0.003)

0.002

0.002

0.002

(0.002)(0.002)(0.002)-0.022-0.019-0.019(0.046)(0.045)(0.045)-0.000-0.016-0.019(0.034)(0.034)(0.034)0.011-0.013-0.015(0.045)(0.045)(0.045)

Educational attainments of parent
Mother: Junior college or specialized school graduate
Mother: University graduate or more
Father: Junior college or specialized school graduate
Father: University graduate or more

-0.041-0.044(0.033)(0.034)-0.076-0.068(0.049)(0.053)-0.132**-0.128**(0.054)(0.053)-0.131*** -0.130***(0.028)(0.029)

Educational attainments of grandparent
Grandfather on father's side: Junior college or specialized school graduate-0.043(0.065)Grandfather on father's side: University graduate or more

0.018
(0.056)Grandmother on father's side: Junior college or specialized school graduate

0.111**(0.056)Grandmother on father's side: University graduate or more

-0.239(0.163)

Grandfather on mother's side: Junior college or specialized school graduate

0.015(0.057)

Grandfather on mother's side: University graduate or more

0.017
(0.052)Grandmother on mother's side: Junior college or specialized school graduate-0.000(0.054)Grandmother on mother's side: University graduate or more

-0.460**(0.217)

Estimation method
Log pseudolikelihood

Logit

Logit

Logit

Logit

Logit

-974.313-965.566-963.685-943.993-936.463

Observations

1,530

1,530

1,530

1,530

1,530

Notes: *, **, and *** denote significance at the 10%, 5%, and 1% levels, respectively.
24